BrightBeat : effortlessly influencing breathing for cultivating calmness and focus

There are many health-related risks associated with chronic stress. One approach for addressing this issue comes from strengthening inside self-regulation abilities rather than eliminating outside sources of stress. However, technology has not been explored to its full potential for delivering calming interventions. While many of the persuasive technologies developed for fostering behavior change focus on cognitive processes, little attention has been given to influencing behavior through automatic processes of the brain. Considering the bidirectional relationship between psycho-physiological signals and self-reported emotional states, manipulating the physiological signals that a human being has voluntary control over is promising for achieving a desired emotional state. In this work, we focus on respiration due to the fact that it is both a voluntary and involuntary response of the body. It is a good indicator of stress, but can also be manipulated to induce calmness. This thesis introduces BrightBeat: a set of seamless visual, auditory, and tactile interventions that mimic a calming breathing oscillation with the aim of influencing physiological syncing and consequently bringing a sense of focus and calmness. These interventions are designed to run easily on commonplace personal electronic devices, respect the user's privacy, and to not require constant focus or attention in order to be effective. We have designed BrightBeat interventions iteratively and have examined both objective and subjective measures of impact through a series of studies with N=54 users in total. From an objective perspective, BrightBeat interventions significantly influenced calmer (slower) breathing and had a lasting influence. From a subjective perspective, considering the individual differences, these interventions have been shown to improve self-reported calmness and focus. Also, participants reported high preference for using them in the future. This work has been supported by the Robert Wood Johnson Foundation and the MIT Media Lab Consortium.

Department dc:contributor.department

Program in Media Arts and Sciences (Massachusetts Institute of Technology)

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Ghandeharioun, Asma

Advisor dc:contributor.advisor

• Rosalind W. Picard.

• Program in Media Arts and Sciences ()

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/107569

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/107569